BACKGROUND: The high rate of repeat attempts among individuals who have previously attempted suicide presents a critical challenge in public health and suicide prevention. While early and targeted intervention is crucial for this high-risk group, eff...
Large language models (LLMs) show potential for medical education, but their domain-specific capabilities need systematic evaluation. This study presents a comparative assessment of thirteen LLMs in urinary system histology education. Using a multi-d...
Earthquakes are one of the most destructive natural disasters that pose a serious threat to human life and infrastructure worldwide. The aim of this study is to evaluate the coping strategies of adult individuals in Turkey regarding earthquake stress...
Mass spectrometry‑based proteomics using isobaric labeling technology has become popular for proteomic quantitation. Existing approaches rely on the mechanism of target-decoy search and false discovery rate control to examine whether a peptide-spectr...
Precise and early detection and diagnosis of lung diseases reduce the severity of life risk and further spread of infections in patients. Computer-based image processing techniques utilize magnetic resonance imaging (MRI) as input for computing, dete...
Colorectal cancer (CRC) is a major global health issue. Despite advancements in treatment, CRC patients still face challenges of metastasis and variable prognosis. Circulating tumor cells (CTCs) shed from the primary tumor into the peripheral blood c...
Gliomas are known to have different sub-regions within the tumor, including the edema, necrotic, and active tumor regions. Segmenting of these regions is very important for glioma treatment decisions and management. This paper aims to demonstrate the...
Opinion mining is more challenging than it was before because of all the user-generated material on social media. People use Twitter (X) to gather opinions on products, advancements, and laws. Sentiment Analysis (SA) examines people's thoughts, feeli...
This study aimed to develop and evaluate deep convolutional neural network (DCNN) models with Grad-CAM visualization for the automated classification with interpretability of tongue conditions-specifically glossitis and oral squamous cell carcinoma (...
AI has propelled the potential for moving toward personalized health and early prediction of diseases. Unfortunately, a significant limitation of many of these deep learning models is that they are not interpretable, restricting their clinical utilit...
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